<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-2EXW46JU</identifier><date>2025</date><creator>Hassan, Oukhouya Mohamed</creator><relation>documents/doc/2/URN_NBN_SI_doc-2EXW46JU_001.pdf</relation><relation>documents/doc/2/URN_NBN_SI_doc-2EXW46JU_001.txt</relation><format format_type="issue">14</format><format format_type="volume">49</format><format format_type="type">article</format><format format_type="extent">str. 193-201</format><identifier identifier_type="DOI">10.31449/inf.v49i14.5751</identifier><identifier identifier_type="ISSN">1854-3871</identifier><identifier identifier_type="COBISSID">242999555</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-2EXW46JU</identifier><language>eng</language><publisher publisher_location="Ljubljana">Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">ARDL</subject><subject language_type_id="slv">COVID-19</subject><subject language_type_id="slv">globoko učenje</subject><subject language_type_id="slv">LSTM</subject><subject language_type_id="slv">Maroko</subject><subject language_type_id="slv">umetna inteligenca</subject><subject language_type_id="slv">XGBoost</subject><title>Comparative analysis of ARDL, LSTM, and XGboost models for forecasting the moroccan stock market during the COVID-19 pandemic</title></Record>